Exploring Convection-Allowing Model Evaluation Strategies for Severe Local Storms Using the Finite-Volume Cubed-Sphere (FV3) Model Core

2021 ◽  
Vol 36 (1) ◽  
pp. 3-19
Author(s):  
Burkely T. Gallo ◽  
Jamie K. Wolff ◽  
Adam J. Clark ◽  
Israel Jirak ◽  
Lindsay R. Blank ◽  
...  
Keyword(s):  
Finite Volume ◽  
Weather Forecasting ◽  
Severe Weather ◽  
Receiver Operating Curve ◽  
Brier Score ◽  
Dynamical Core ◽  
Object Based ◽  
Verification Methods ◽  
Cubed Sphere ◽  
Verification Techniques

AbstractVerification methods for convection-allowing models (CAMs) should consider the finescale spatial and temporal detail provided by CAMs, and including both neighborhood and object-based methods can account for displaced features that may still provide useful information. This work explores both contingency table–based verification techniques and object-based verification techniques as they relate to forecasts of severe convection. Two key fields in severe weather forecasting are investigated: updraft helicity (UH) and simulated composite reflectivity. UH is used to generate severe weather probabilities called surrogate severe fields, which have two tunable parameters: the UH threshold and the smoothing level. Probabilities computed using the UH threshold and smoothing level that give the best area under the receiver operating curve result in very high probabilities, while optimizing the parameters based on the Brier score reliability component results in much lower probabilities. Subjective ratings from participants in the 2018 NOAA Hazardous Weather Testbed Spring Forecasting Experiment (SFE) provide a complementary evaluation source. This work compares the verification methodologies in the context of three CAMs using the Finite-Volume Cubed-Sphere Dynamical Core (FV3), which will be the foundation of the U.S. Unified Forecast System (UFS). Three agencies ran FV3-based CAMs during the five-week 2018 SFE. These FV3-based CAMs are verified alongside a current operational CAM, the High-Resolution Rapid Refresh version 3 (HRRRv3). The HRRR is planned to eventually use the FV3 dynamical core as part of the UFS; as such evaluations relative to current HRRR configurations are imperative to maintaining high forecast quality and informing future implementation decisions.

scholarly journals Application of Two Spatial Verification Methods to Ensemble Forecasts of Low-Level Rotation

2016 ◽  
Vol 31 (3) ◽  
pp. 713-735 ◽  
Author(s):  
Patrick S. Skinner ◽  
Louis J. Wicker ◽  
Dustan M. Wheatley ◽  
Kent H. Knopfmeier
Keyword(s):  
Displacement Component ◽  
Ensemble Forecasts ◽  
Matching Algorithm ◽  
Low Level ◽  
Object Based ◽  
Verification Methods ◽  
Ensemble Mean ◽  
Dimensional Object ◽  
Verification Techniques ◽  
Spatial Verification

Abstract Two spatial verification methods are applied to ensemble forecasts of low-level rotation in supercells: a four-dimensional, object-based matching algorithm and the displacement and amplitude score (DAS) based on optical flow. Ensemble forecasts of low-level rotation produced using the National Severe Storms Laboratory (NSSL) Experimental Warn-on-Forecast System are verified against WSR-88D single-Doppler azimuthal wind shear values interpolated to the model grid. Verification techniques are demonstrated using four 60-min forecasts issued at 15-min intervals in the hour preceding development of the 20 May 2013 Moore, Oklahoma, tornado and compared to results from two additional forecasts of tornadic supercells occurring during the springs of 2013 and 2014. The object-based verification technique and displacement component of DAS are found to reproduce subjectively determined forecast characteristics in successive forecasts for the 20 May 2013 event, as well as to discriminate in subjective forecast quality between different events. Ensemble-mean, object-based measures quantify spatial and temporal displacement, as well as storm motion biases in predicted low-level rotation in a manner consistent with subjective interpretation. Neither method produces useful measures of the intensity of low-level rotation, owing to deficiencies in the verification dataset and forecast resolution.

Beyond the Basics: Evaluating Model-Based Precipitation Forecasts Using Traditional, Spatial, and Object-Based Methods

2014 ◽  
Vol 29 (6) ◽  
pp. 1451-1472 ◽  
Author(s):  
Jamie K. Wolff ◽  
Michelle Harrold ◽  
Tressa Fowler ◽  
John Halley Gotway ◽  
Louisa Nance ◽  
...  
Keyword(s):  
Mesoscale Model ◽  
Skill Score ◽  
Careful Consideration ◽  
Diagnostic Information ◽  
Coverage Area ◽  
Object Based ◽  
Grid Approach ◽  
Verification Methods ◽  
Verification Techniques ◽  
Spatial Verification

Abstract While traditional verification methods are commonly used to assess numerical model quantitative precipitation forecasts (QPFs) using a grid-to-grid approach, they generally offer little diagnostic information or reasoning behind the computed statistic. On the other hand, advanced spatial verification techniques, such as neighborhood and object-based methods, can provide more meaningful insight into differences between forecast and observed features in terms of skill with spatial scale, coverage area, displacement, orientation, and intensity. To demonstrate the utility of applying advanced verification techniques to mid- and coarse-resolution models, the Developmental Testbed Center (DTC) applied several traditional metrics and spatial verification techniques to QPFs provided by the Global Forecast System (GFS) and operational North American Mesoscale Model (NAM). Along with frequency bias and Gilbert skill score (GSS) adjusted for bias, both the fractions skill score (FSS) and Method for Object-Based Diagnostic Evaluation (MODE) were utilized for this study with careful consideration given to how these methods were applied and how the results were interpreted. By illustrating the types of forecast attributes appropriate to assess with the spatial verification techniques, this paper provides examples of how to obtain advanced diagnostic information to help identify what aspects of the forecast are or are not performing well.

A Two-Way Nested Global-Regional Dynamical Core on the Cubed-Sphere Grid

2013 ◽  
Vol 141 (1) ◽  
pp. 283-306 ◽  
Author(s):  
Lucas M. Harris ◽  
Shian-Jiann Lin
Keyword(s):  
Finite Volume ◽  
Large Scale ◽  
Wave Train ◽  
Mass Conservation ◽  
Volume Averaging ◽  
Test Case ◽  
Geophysical Fluid Dynamics Laboratory ◽  
Dynamical Core ◽  
Nested Grid ◽  
Cubed Sphere

Abstract A nested-grid model is constructed using the Geophysical Fluid Dynamics Laboratory finite-volume dynamical core on the cubed sphere. The use of a global grid avoids the need for externally imposed lateral boundary conditions, and the use of the same governing equations and discretization on the global and regional domains prevents inconsistencies that may arise when these differ between grids. A simple interpolated nested-grid boundary condition is used, and two-way updates use a finite-volume averaging method. Mass conservation is achieved in two-way nesting by simply not updating the mass field. Despite the simplicity of the nesting methodology, the distortion of the large-scale flow by the nested grid is such that the increase in global error norms is a factor of 2 or less in shallow-water test cases. The effect of a nested grid in the tropics on the zonal means and eddy statistics of an idealized Held–Suarez climate integration is minor, and artifacts due to the nested grid are comparable to those at the edges of the cubed-sphere grid and decrease with increasing resolution. The baroclinic wave train in a Jablonowski–Williamson test case was preserved in a nested-grid simulation while finescale features were represented with greater detail in the nested-grid region. The authors also found that lee vortices could propagate out of the nested region and onto a coarse grid, which by itself could not produce vortices. Finally, the authors discuss how concurrent integration of the nested and coarse grids can be significantly more efficient than when integrating the two grids sequentially.

Formal Verification of Control System Software

2019 ◽  
Author(s):  
Pierre-Loïc Garoche
Keyword(s):  
Control System ◽  
Formal Verification ◽  
Formal Analysis ◽  
Critical Systems ◽  
System Software ◽  
Unified Approach ◽  
Verification Methods ◽  
Autonomous Cars ◽  
Computer Scientists ◽  
Verification Techniques

The verification of control system software is critical to a host of technologies and industries, from aeronautics and medical technology to the cars we drive. The failure of controller software can cost people their lives. This book provides control engineers and computer scientists with an introduction to the formal techniques for analyzing and verifying this important class of software. Too often, control engineers are unaware of the issues surrounding the verification of software, while computer scientists tend to be unfamiliar with the specificities of controller software. The book provides a unified approach that is geared to graduate students in both fields, covering formal verification methods as well as the design and verification of controllers. It presents a wealth of new verification techniques for performing exhaustive analysis of controller software. These include new means to compute nonlinear invariants, the use of convex optimization tools, and methods for dealing with numerical imprecisions such as floating point computations occurring in the analyzed software. As the autonomy of critical systems continues to increase—as evidenced by autonomous cars, drones, and satellites and landers—the numerical functions in these systems are growing ever more advanced. The techniques presented here are essential to support the formal analysis of the controller software being used in these new and emerging technologies.

Severe-Weather Forecasting

Science ◽  
1965 ◽  
Vol 149 (3687) ◽  
pp. 924-924
Author(s):  
W. S. Barney
Keyword(s):  
Weather Forecasting ◽  
Severe Weather

Transport Schemes in GungHo

2021 ◽  
Author(s):  
James Kent
Keyword(s):  
Finite Element ◽  
Finite Volume ◽  
Mixed Finite Element ◽  
Method Of Lines ◽  
Finite Volume Methods ◽  
Kutta Method ◽  
Finite Volume Schemes ◽  
Dynamical Core ◽  
Runge Kutta Method ◽  
The Stability

<p>GungHo is the mixed finite-element dynamical core under development by the Met Office. A key component of the dynamical core is the transport scheme, which advects density, temperature, moisture, and the winds, throughout the atmosphere. Transport in GungHo is performed by finite-volume methods, to ensure conservation of certain quantaties. There are a range of different finite-volume schemes being considered for transport, including the Runge-Kutta/method-of-lines and COSMIC/Lin-Rood schemes. Additional horizontal/vertical splitting approaches are also under consideration, to improve the stability aspects of the model. Here we discuss these transport options and present results from the GungHo framework, featuring both prescribed velocity advection tests and full dry dynamical core tests. </p>

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